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@helloromero
helloromero / rasp_pi__zero_config_from_scratch.md
Created November 19, 2025 00:06 — forked from axelhamil/rasp_pi__zero_config_from_scratch.md
🚀 Raspberry Pi Zero 2 W – Headless Setup Guide (with Static IP) and Pi Hole

Raspberry Pi OS SSH Ready

A quick and clean guide to set up your Raspberry Pi Zero 2 W headlessly with Wi-Fi, SSH, and a static IP – perfect for IoT and embedded projects.


🧰 Requirements

@JRex286
JRex286 / vbios-comparison-table.md
Created June 25, 2026 01:23
GA100 VBIOS Comparison Table — CMP 170HX vs A100 PCIe vs Drive A100 (7 bytes of deliberate restriction)

GA100 VBIOS Comparison Table

Cross-variant comparison of VBIOS structure and configuration across the GA100 product family. Sourced from static binary analysis of ROM dumps + empirical flash experiments + Lapsus Booter disassembly.

Last updated: 2026-05-31 (Drive A100 PG199 VBIOS dumped and analyzed)

Contributors: Petri Krohn (ECB cryptanalysis, RFRD manifest decode, known-plaintext identification), Cab (ECB padding block confirmation, ImHex structure labeling, license region offset discovery via gpuio BAR0 dump)

Table of contents

Polymarket BTC 5-Minute Up/Down Trading Bot — Build Guide

What This Bot Does

This bot trades Polymarket's "BTC Up or Down" 5-minute binary markets. Every 5 minutes, Polymarket opens a market asking: "Will BTC be higher or lower than the opening price when this 5-minute window closes?" You buy "Up" or "Down" tokens at some price (e.g. $0.50–$0.95), and if you're right, each token pays out $1.00. If you're wrong, you lose your bet.

The bot uses technical analysis on real-time Binance BTC price data to predict the outcome, then places the trade on Polymarket right before the window closes — when we have the most information but (ideally) before the token price has fully priced in the outcome.


@timvisee
timvisee / falsehoods-programming-time-list.md
Last active July 22, 2026 19:53
Falsehoods programmers believe about time, in a single list

Falsehoods programmers believe about time

This is a compiled list of falsehoods programmers tend to believe about working with time.

Don't re-invent a date time library yourself. If you think you understand everything about time, you're probably doing it wrong.

Falsehoods

  • There are always 24 hours in a day.
  • February is always 28 days long.
  • Any 24-hour period will always begin and end in the same day (or week, or month).
@vadymhimself
vadymhimself / unit-tests.md
Last active July 22, 2026 19:50
Writing Great Unit Tests: Best and Worst Practices

This blog post is aimed at developers with at least a small amount of unit testing experience. If you've never written a unit test, please read an introduction and have a go at it first.

What's the difference between a good unit test and a bad one? How do you learn how to write good unit tests? It's far from obvious. Even if you're a brilliant coder with decades of experience, your existing knowledge and habits won't automatically lead you to write good unit tests, because it's a different kind of coding and most people start with unhelpful false assumptions about what unit tests are supposed to achieve.

Most of the unit tests I see are pretty unhelpful. I'm not blaming the developer: Usually, he or she just got told to start unit testing, so they installed NUnit

@VictorTaelin
VictorTaelin / solving_the_mystery.md
Last active July 22, 2026 19:47
Solving the mystery behind Abstract Algorithm’s magical optimizations

Note: This is an old post from back when I was trying to make sense of why inets are so fast for evaluating some λ-terms. It has some silly bits, I learned a lot since and could probably write a better article today, but I think this can still be insightful for these getting started, so I'll leave it here.

Yesterday, I reported the bizarre observation that certain functions can behave as if they had negative complexity. If you haven’t checked that article yet, it isn’t necessary, but you should, as it may blow your mind. In short, the λ-term f(bits) = copy(comp(inc,n,bits)), when given to optimal λ-calculus evaluator, is asymptotically faster than g(bits) = comp(inc,n,bits); i.e.,copy (a O(1) operation for a fixed size) behaves as if it had a O(1/n) complexity, causing the program to run faster by doing more things (!?).

That’s not the only bizarre complexity result I had when

@Chenx221
Chenx221 / recovery.json, cloudready_recovery.json
Last active July 22, 2026 19:46
Chrome OS recovery images manual download (Flex)
# Chrome OS recovery images manual download
https://dl.google.com/dl/edgedl/chromeos/recovery/recovery2.json
https://dl.google.com/dl/edgedl/chromeos/recovery/recovery.json
# Google Chrome OS Flex images manual download
https://dl.google.com/dl/edgedl/chromeos/recovery/cloudready_recovery2.json
https://dl.google.com/dl/edgedl/chromeos/recovery/cloudready_recovery.json

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.